Locate connected regions of a specified color in an image, returning bounding boxes, area share, and centroids plus total coverage. Use it to identify objects before editing.
Where does a colour occur? Returns connected regions (bbox, share, centroid), largest first, plus total coverage. Good for locating objects before editing them.
| Name | Required | Description | Default |
|---|---|---|---|
| x | No | ||
| y | No | ||
| color | Yes | ||
| layer | No | ||
| limit | No | ||
| width | No | ||
| height | No | ||
| tolerance | No |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and no output schema, the description usefully discloses the response structure and ordering ('connected regions... largest first, plus total coverage'), which the agent would otherwise have to guess. It stops short of behavioural detail: nothing about how tolerance affects region merging, what limit truncates, or whether omitted x/y/width/height default to the whole canvas.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with the core question front-loaded and the return shape immediately following. The fragment-style opening is slightly cryptic but costs no words that could be spent on parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter tool with zero schema coverage, no annotations, and no output schema, the definition is under-specified: the search scope parameters (x/y/width/height/layer) and tolerance semantics are the main risk of a mis-call and are unaddressed. Only the return value side is adequately covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% across 8 parameters. The description only implicitly covers 'color' and hints at ordering (relevant to 'limit'); x, y, width, height, layer, and tolerance — the parameters that determine search scope and matching strictness — carry no explanation anywhere. This is a substantial gap the description should compensate for but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific operation (finding where a colour occurs) and enumerates the return shape (bbox, share, centroid, largest first, total coverage). It is clearly distinguishable from sample_color or match_colors by describing regions rather than pixel or palette operations, though it never names those siblings explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
One implicit usage cue is given: 'Good for locating objects before editing them.' There is no statement of when not to use it, no mention of alternatives such as sample_color or analyze_image, and no prerequisites or ordering advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.